Machine learning-driven quantitative modeling and mechanistic interpretation of per and poly-fluoroalkyl substances (PFAS) toxicity

Journal of environmental chemical engineering 2026

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Authors: Chenjian Ye, H. Clive Liu, J. Liu, Hailong Wang, Ruijie Ge, Xiaolong Chen, Yuqing Wang, C. N. Wang, Jianzhong Zhu

DOI: 10.1016/j.jece.2026.121063

Cited by: 5

References: 71

Fields of Study & Subjects

Per- and polyfluoroalkyl substances research Effects and risks of endocrine disrupting chemicals Toxic Organic Pollutants Impact

References 71